Object Detection
Back to Home
01. Intro to Vehicle Tracking
02. Arpan and Drew
03. Finding Cars
04. Object Detection Overview
05. Manual Vehicle Detection
06. Features
07. Feature Intuition
08. Color Features
09. Template Matching
10. Template Matching Quiz
11. Color Histogram Features
12. Histograms of Color
13. Histogram Comparison
14. Color Spaces
15. Explore Color Spaces
16. Spatial Binning of Color
17. Gradient Features
18. HOG Features
19. Data Exploration
20. scikit-image HOG
21. Combining Features
22. Combine and Normalize Features
23. Build a Classifier
24. Labeled Data
25. Data Preparation
26. Train a Classifier
27. Parameter Tuning
28. Color Classify
29. HOG Classify
30. Sliding Windows
31. How many windows?
32. Sliding Window Implementation
33. Multi-scale Windows
34. Search and Classify
35. Hog Sub-sampling Window Search
36. False Positives
37. Multiple Detections & False Positives
38. Tracking Pipeline
39. Summary
40. Traditional vs. Deep Learning Approach
Back to Home
40. Traditional vs. Deep Learning Approach
Traditional vs. Deep Learning Approach